The finish of a product or object, such as the visible surface of a painted object, plays an important role in a consumer's perception of the quality of the object. Accordingly, for high quality automobiles and other vehicles and/or articles of manufacture, the inspection of coatings, such as paint coatings, for defects is an important part of quality control. For example, the body panels of an automobile may receive at least four coatings including a protective coat, an adhesion aid coat, a paint coat and a clear coat. Defects occurring in any one of the coatings applied to a properly prepared substrate or surface may diminish a consumer's perception of the automobile. Such defects may include, but are not limited to, dust, hair, metallic particles, coating over spray, incomplete spray, stripping and flake penetration.
In order to identify defects in a coating each coating may be evaluated after application. Previously, evaluation of the quality of a coating was often based on human inspection, which can be a tedious and subjective process which requires meaningful skill and training. Other, automated inspection procedures have been developed which use charge-coupled device (CCD) optical sensors that sense imperfections through light reflected from the coated surface. However, this technique is not particularly effective for complex, curved and/or hidden geometries (i.e. automobile body panels) because of its sensitivity and dependence on reflection and scattering angles.
Other inspection techniques have been developed which use infrared cameras to inspect certain products (i.e. semiconductor chips) for surface anomalies or defects. However, such inspection techniques are based solely on the spatial analysis of pixel values with that of known (standard) values without any account for the temporal behavior of the pixel values (e.g., change of temperature over time). Further, while other techniques have been utilized to measure the change of temperature over time, such techniques do not compare the measured change of temperature of pixels to that of surrounding pixels, and therefore fail to efficiently and effectively detect subsurface anomalies. Moreover, many inspection procedures require comparison to a known non-defective area within a thermal profile for thermal deviation determinations while others require continuous acquisition of a sequence of data files. Such procedures can also require operator intervention, significant time requirements, and/or computational complexities not suited for realtime applications.
Accordingly, a need exists for alternative methods and systems for inspecting a substrate for defects which may be present in a coating applied to the substrate.